IcaSet class is derived from
eSet, and requires a matrix named dat as
assayData member.
eSet.new("IcaSet") new("IcaSet",
annotation = character(0),
experimentData = new("MIAME"),
featureData = new("AnnotatedDataFrame"),
phenoData = new("AnnotatedDataFrame"),
protocolData = phenoData[,integer(0)],
dat = new("matrix"),
A=new("data.frame"),
S=new("data.frame"), ...)
This creates an IcaSet with assayData implicitly
created to contain dat. new("IcaSet",
annotation = character(0),
assayData = assayDataNew(dat=new("matrix")),
experimentData = new("MIAME"),
featureData = new("AnnotatedDataFrame"),
phenoData = new("AnnotatedDataFrame"),
protocolData = phenoData[,integer(0)],
A=new("data.frame"),
S=new("data.frame"), ...)
This creates an IcaSet with assayData provided
explicitly. IcaSet instances are usually created through
new("IcaSet", ...). Usually the arguments to new
include dat ('features x samples', e.g a matrix of expression
data), phenoData ('samples x annotations', a
matrix of sample annotations), S the Source
matrix of the ICA decomposition ('features x comp'), A the Mixing matrix of the ICA
decomposition ('samples x comp'), annotation the annotation
package, typeID the description of the feature and gene IDs. The other attributes can be missing, in which case
they are assigned default values. The function buildIcaSet is a more convenient way to
create IcaSet instances, and allows to automatically annotate
the features.eSet:
annotation:eSetassayData:nrow(phenoData). assayData must contain a matrix
dat with rows representing features (e.g., reporters)
and columns representing samples. Class:AssayData-classexperimentData:eSetfeatureData:eSetphenoData:eSetprotocolData:eSetorganism:chipManu="illumina"
mart:useMart of package biomaRt. Only useful if no annotation package is available for argument icaSet.
datByGene:dat where
features have been replaced by their annotations (e.g, gene IDs). Rows
represent annotations of the features (e.g., gene IDs) and
columns represent samples.A:nrow(phenoData) (dimension: 'samples x comp').S:nrow(assayData) (dimension: 'features x comp').SByGene:nrow(datByGene) (dimension: 'annotatedFeatures x comp').compNames:indComp:witGenes:chipManu:chipVersion:chipManu="illumina"refSamples:sampleNames(object), i.e in colnames(dat).typeID:datByGene and SByGene of the icaSet.
It must match one of the objects the corresponding package supports
(you can access the list of objects by typing ls("package:packagename")). If
no annotation package is provided, this element is not useful.listFilters(mart); where mart is specified as described in useMart.
If you have directly built the IcaSet at the
gene level (i.e if no annotation package is used), featureID_biomart and
geneID_biomart will be identical.listFilters(mart); where
mart is specified as described in function useMart.
Not useful if you work at the gene level.getComp(IcaSet, ind,
level=c("features","genes"))level="features") or gene (level="genes")
projections from S. Returns a list with two elements:
contrib the sample contributions and proj the
feature or gene projections.slotName(IcaSet), and
slotName(IcaSet)<-:slotName contained in an IcaSet object.IcaSet["slotName"], and
IcaSet["slotName"]<-:slotName contained in an IcaSet object.A(IcaSet), and
A(IcaSet)<-:A.S(IcaSet), and
S(IcaSet)<-:S.Slist(IcaSet):SByGene(IcaSet), and
SByGene(IcaSet)<-:SByGene.SlistByGene(IcaSet):organism(IcaSet), organism(IcaSet,characte)<-organism slot.dat(IcaSet), dat(IcaSet,matrix)<-dat in the AssayData-class
slot.eSet:
pData(IcaSet), pData(IcaSet,value)<-:eSetassayData(IcaSet):eSetsampleNames(IcaSet) and sampleNames(IcaSet)<-:eSetfeatureNames(IcaSet), featureNames(IcaSet, value)<-:eSetdims(IcaSet):eSetphenoData(IcaSet), phenoData(IcaSet,value)<-:eSetvarLabels(IcaSet), varLabels(IcaSet, value)<-:eSetvarMetadata(IcaSet), varMetadata(IcaSet,value)<-:eSetvarMetadata(IcaSet), varMetadata(IcaSet,value)eSetexperimentData(IcaSet),experimentData(IcaSet,value)<-:eSetpubMedIds(IcaSet), pubMedIds(IcaSet,value)eSetabstract(IcaSet):eSetannotation(IcaSet), annotation(IcaSet,value)<-eSetprotocolData(IcaSet), protocolData(IcaSet,value)<-eSetcombine(IcaSet,IcaSet):eSetstorageMode(IcaSet), storageMode(IcaSet,character)<-:eSetinitialize(IcaSet):new; not to be called directly by the user.validObject(IcaSet):dat is a member of
assayData, and that the number of features, genes, samples,
and components are consistent across all the attributes of the
IcaSet object. checkValidity(IcaSet) imposes this
validity check, and the validity checks of eSet.IcaSet[slotName], IcaSet[slotName]<-:slotName contained in an
IcaSet object.IcaSet[i, j, k]:makeDataPackage(object, author, email, packageName, packageVersion, license, biocViews, filePath, description=paste(abstract(object), collapse="\n\n"), ...)makeDataPackage.show(IcaSet):eSetdim(IcaSet), ncol:eSetIcaSet[(index)]:eSetIcaSet$, IcaSet$<-:eSetIcaSet[[i]], IcaSet[[i]]<-:eSeteSet-class, buildIcaSet,
IcaSet-class, MineICAParams-class.
# create an instance of IcaSet
new("IcaSet")
dat <- matrix(runif(100000), nrow=1000, ncol=100)
rownames(dat) <- 1:nrow(dat)
new("IcaSet",
dat=dat,
A=as.data.frame(matrix(runif(1000), nrow=100, ncol=10)),
S=as.data.frame(matrix(runif(10000), nrow=1000, ncol=10), row.names = 1:nrow(dat)))
Run the code above in your browser using DataLab